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University College London

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Research Assistant / Research Fellow in Computational Statistics and Machine Learning at University College London University College London in United Kingdom

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Jul 31, 2026

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Country

United Kingdom

University

University College London

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Keywords

Computer Science
Mathematics
Computational Statistics
Statistics
Machine learning

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About this position

University College London (UCL), Department of Statistical Science, is advertising a short-term research opportunity in computational statistics and machine learning with the Fundamentals of Statistical Machine Learning research group.

The role is based in London, United Kingdom and runs from January to August 2027 (8 months). It is described as a research position suitable for several profiles: a strong MSc student preparing for a PhD, a current PhD student seeking a research visit, or a finishing PhD student / post-PhD candidate looking for a first position. The post is framed as a Research Assistant (pre-PhD) or Research Fellow (post-PhD) opportunity.

The research focus is at the intersection of statistics, machine learning, and AI, with the successful candidate joining a group working on the theoretical and applied foundations of statistical machine learning. The post is especially relevant for applicants interested in statistical science, computational methods, and related quantitative research areas.

Eligibility highlights: applicants should be in or near MSc/PhD stages, or have recently completed a PhD; the post is aimed at candidates in Statistics, ML, or related fields. The post mentions that there may be a real possibility of extension through further funding, but no specific salary, stipend, tuition, or scholarship details are provided in the post text.

Deadline: 31 July 2026.

How to apply: read the full job description, then apply through the official UCL portal using the application link. The FSML group page is also provided for more context about the research group.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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